4.4 Article

Reasons for prolonged time for diagnostic workup for stage I-II lung cancer and estimated effect of applying an optimized pathway for diagnostic procedures

Journal

BMC HEALTH SERVICES RESEARCH
Volume 19, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12913-019-4517-z

Keywords

Pathway; Timeliness; Diagnostic efficacy; Organization

Funding

  1. St Olavs hospital

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Background Minimizing the time until start of cancer treatment is a political goal. In Norway, the target time for lung cancer is 42 days. The aim of this study was to identify reasons for delays and estimate the effect on the timelines when applying an optimal diagnostic pathway. Methods Retrospective review of medical records of lung cancer patients, with stage I-II at baseline CT, receiving curative treatment (n = 100) at a regional cancer center in Norway. Results Only 40% started treatment within 42 days. The most important delays were late referral to PET CT (n = 27) and exercise test (n = 16); repeated diagnostic procedures because bronchoscopy failed (n = 15); and need for further investigations after PET CT (n = 11). The time from referral to PET CT until the final report was 20.5 days in median. Applying current waiting time for PET CT (<= 7 days), 48% would have started treatment within 42 days (p = 0.254). Optimal pathway was defined as 1) referral to PET CT and exercise test immediately after the CT scan and hospital visit, 2) tumor board discussion to decide diagnostic strategy and treatment, 3) referral to surgery or curative radiotherapy, 4) tissue sampling while waiting to start treatment. Applying the optimal pathway, current waiting time for PET CT and observed waiting times for the other procedures, 80% of patients could have started treatment within 42 days (p < 0.001), and the number of tissue sampling procedures could have been reduced from 112 to 92 (- 16%). Conclusion Changing the sequence of investigations would significantly reduce the time until start of treatment in curative lung cancer patients at our hospital and reduce the resources needed.

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